ABSTRACT
ABSTRACT This study is intended to verify validity of an efficient damage detection method by means of a Bayesian approach. A Bayesian inference was adopted to the regressive model representing bridge vibration. The posterior distribution for the regressive coefficients provides reasonable damage-sensitive features. Bayesian hypothesis testing is formulated using a Bayes factor, which is defined as a ratio of marginalized likelihoods to detect anomaly in the damage-sensitive features. Feasibility of the proposed method is examined via a half-year monitoring experiment on a steel plate girder bridge. The proposed method efficiently detected the seasonal fluctuation in the modal properties. The feasibility was also examined through a field experiment with artificial damages imitating fatigue cracks.
